Discover how innovations in LLMs are revolutionizing support for low-resource languages, bridging linguistic gaps, and fostering inclusivity in AI inclusivity.

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The article explores challenges faced by low resource languages in accessing large language models (LLMs) and presents innovative strategies, like creating high-quality fine-tuning datasets, to improve LLM performance, particularly focusing on Swahili as a case study. These advancements contribute to a more inclusive AI ecosystem, supporting linguistic diversity and accessibility.